Comprehensive review of artificial neural network applications to pattern recognition
The era of artificial neural network (ANN) began with a simplified application in many fields
and remarkable success in pattern recognition (PR) even in manufacturing industries …
and remarkable success in pattern recognition (PR) even in manufacturing industries …
Fuzzy control and filtering for nonlinear singularly perturbed Markov jump systems
This article addresses the H_∞ control and filtering problems for Markov jump singularly
perturbed systems approximated by Takagi-Sugeno fuzzy models. The underlying transition …
perturbed systems approximated by Takagi-Sugeno fuzzy models. The underlying transition …
RNN for perturbed manipulability optimization of manipulators based on a distributed scheme: A game-theoretic perspective
In order to leverage the unique advantages of redundant manipulators, avoiding the
singularity during motion planning and control should be considered as a fundamental issue …
singularity during motion planning and control should be considered as a fundamental issue …
Neural-network-based adaptive control of uncertain MIMO singularly perturbed systems with full-state constraints
H Wang, C Yang, X Liu, L Zhou - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
This article investigates the tracking control problem for a class of nonlinear multi-input–multi-
output (MIMO) uncertain singularly perturbed systems (SPSs) with full-state constraints. The …
output (MIMO) uncertain singularly perturbed systems (SPSs) with full-state constraints. The …
A weight perturbation-based regularisation technique for convolutional neural networks and the application in medical imaging
A convolutional neural network has the capacity to learn multiple representation levels and
abstraction in order to provide a better understanding of image data. In addition, a good …
abstraction in order to provide a better understanding of image data. In addition, a good …
A multi-constrained zeroing neural network for time-dependent nonlinear optimization with application to mobile robot tracking control
Because of the strong dynamic behavior and computing power, zeroing neural networks
(ZNNs) have been dee different time-dependent issues. However, due to the high …
(ZNNs) have been dee different time-dependent issues. However, due to the high …
Improved learning algorithm for two-layer neural networks for identification of nonlinear systems
This study is concerned with the asymptotic identification of nonlinear systems based on
Lyapunov theory and two-layer neural networks. An improved identification model enhanced …
Lyapunov theory and two-layer neural networks. An improved identification model enhanced …
Neural network-based iterative learning control of a piezo-driven nanopositioning stage
The piezo-driven nanopositioning stage (PNS) is a key device to provide fast and precise
motions for applications such as micromanipulation, microfabrication, and microscopy …
motions for applications such as micromanipulation, microfabrication, and microscopy …
Adaptive optimal tracking controls of unknown multi-input systems based on nonzero-sum game theory
This paper focuses on the optimal tracking control problem (OTCP) for the unknown multi-
input system by using a reinforcement learning (RL) scheme and nonzero-sum (NZS) game …
input system by using a reinforcement learning (RL) scheme and nonzero-sum (NZS) game …
Identification and control of nonlinear systems using neural networks: A singularity-free approach
In this paper, identification and control for a class of nonlinear systems with unknown
constant or variable control gains are investigated. By reformulating the original system …
constant or variable control gains are investigated. By reformulating the original system …